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Ishango Data science Fellowship
Ishango Data science Fellowship

Join our Data Science Programme

Accelerate your career by working on real-world projects for international companies. You will receive a generous stipend, gain access to mentors from global institutions, and receive training to enhance your professional skills. Apply below if you are a recent African graduate with a degree in Mathematics, Computer Science, Engineering, Physics, and Statistics or have at least 2 years of data science experience and excellent Python coding skills.

Apply now

Join our Data Science Programme

Accelerate your career by working on real-world projects for international companies. You will receive a generous stipend, gain access to mentors from global institutions, and receive training to enhance your professional skills. Apply below if you are a recent African graduate with a degree in Mathematics, Computer Science, Engineering, Physics, and Statistics or have at least 2 years of data science experience and excellent Python coding skills.

Apply now

Why Join our Programme?

Fully funded & free

Master marketing your skills to a global audience at no cost to yourself.

Learn as part of a team

Train, work, and network with your cohort, support and celebrate each other's success.

Work with global companies

Gain experience on projects from top global companies and seek guidance from experienced mentors.

Submit your application

Here are two examples of successfully completed projects done by Ishango Data Scientists during our Data Science Programme.

Faith and Cyrille presenting their project on an unsupervised predictor model developed in collaboration with Elder Research

Anisie and Joseph presenting their project on machine learning model to predict mental health illness developed in collaboration with Omniscient Neurotechnology

Meet Our Data Scientists

Naftali Indongo

Naftali has an honours degree in applied mathematics from the University of Namibia and a master’s degree from the African Institute for Mathematical Sciences (AIMS). He then pursued an MSc in machine learning and artificial intelligence from Stellenbosch University.
 

Sharleen Muoki

Sharleen holds a bachelor’s in Business Intelligence and a master’s in Business Intelligence and Data Analytics from Strathmore University.

Stephen Adjignon

Stephen has a High National Diploma in Production Engineering from Ho Technical University. 
 

Luel Hagos

Luel has a master’s in Mathematical Sciences with a focus on data science from African Institute of Mathematical Sciences in Rwanda.
 

Shadrack Darku

Shadrack holds a bachelor’s degree in Telecommunications Engineering from Kwame Nkrumah University of Science and Technology

Vincent Adunna Frimpong

He holds a BSc. in statistics from the University of Ghana. In his professional journey, he has gained over four years of experience as a software engineer, leading projects in software migration, systems integration, report building, and open-source projects.

Samuel Gyimah

Samuel has a Bachelor of Science in Mechanical Engineering from the University of Energy and Natural Resources, Ghana. 

Cyrille Feudjio

Cyrille holds Master’s Degree in Industrial Mathematics from AIMS Cameroon, an Engineer’s Degree in Industrial Engineering and a Masters in Physics from the University of Dschang.

Nana Yaw Agyeman

Nana Yaw holds a bachelor’s in Computer Engineering from the University of Ghana and a master’s in Computer Science from Anglia Ruskin University.

Mahamat Azibert

Mahamat has a bachelor’s in Applied Mathematics from the University of Dschang and a Master’s in applied mathematics from the African Institute for Mathematical Sciences (AIMS).

Opanin Agyei Adu

Opanin has a Master’s of Philosophy in applied mathematics from Kwame Nkrumah University of Science and a Bachelor of Science in Statistics.


FAQs

We also welcome applicants from engineering and statistics backgrounds, as well as applicants with any degree who can demonstrate at least 2 years of relevant work experience and have successfully completed online courses in data science.

Complete and submit the online application form. If you meet all the requirements, you will be invited to complete an online technical assessment. If successful, you will be invited for a technical interview, after which you will be shortlisted and invited for a client interview once you are matched to a project. You will receive a confirmed offer upon successfully completing the client interview.

We look for people that have data science and problem-solving skills, a good level of coding, work well as part of a team, and have good time management and planning skills.
Yes, you can reapply when you are ready.

No. Candidates will start working on real projects immediately after they have been accepted. It is therefore expected that you would have the fundamentals of programming and have completed courses on data science basics (e.g., DataCamp, DataQuest, Udemy, Coursera, etc.) to a good level before applying.

It is not possible to join the programme part-time or on flexible hours. Working with Ishango is a full-time and remote opportunity. It is therefore essential that you only accept an offer if they can commit full-time and have good and stable internet access to work remotely.
Ideally yes, but you can still apply if you are an African schooling abroad and intending to go back.
 
The programme is an opportunity for you to demonstrate your skills and impress your host company. If a host company is happy with your performance they may offer you a contract to continue working with them. We will also provide you with further support and exposure to help you with your job search.
Projects will be all data-based. Each host company proposes a project and you will have to find a solution for it in your team of two. The projects vary considerably depending on the host company, however they all require strong data engineering and data science skills. Tools and skills often required are: machine learning; NLP; working with DBs; Python; VS Code Studio; git.
 
All kinds of companies from all over the world. Most of them are data science-guided, and others are just companies which have proposed data projects with which they need help.
 

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